AI in Your DR – Should You, or Shouldn’t You?

Artificial intelligence is finding its way into many applications and systems, so why not disaster recovery? The advantages are multiple.

AI tools and techniques can automate DR procedures to make them faster than manual intervention, while keeping them reliable and intelligent – for example, by making choices according to incidents or circumstances. They can help estimate times to complete recovery.

Advanced systems can learn from past situations (machine learning) and recognise problems likely to arise in the future, which can then be mitigated or avoided before they happen. However, while AI can help DR performance and results, it is by no means a miracle solution.

Whatever the AI system or support being used for disaster recovery, at some stage, a human being built it. Even machine learning systems that chew through vast amounts of data, automatically picking out patterns and data relationships, were programmed by people. And people are not infallible.

That’s the downside of getting people involved. The upside is that people are naturally creative and innovative, and possess faculties of judgment and decision-making that machines cannot (yet) emulate. Nevertheless, bad programming means bad AI, and from that bad choices about what to recover when, or bad learning about which DR choices are to be preferred.

Currently, artificial intelligence and human intelligence work best together. AI helps by executing DR tasks faster, without mistakes and without omissions. In step by step procedures to recover data, applications and systems, the quasi-infallibility of machines can be invaluable.

Likewise, for constantly checking hundreds, thousands or even more different parameters. By comparison, decisions involving business priorities and balancing of hard to quantify criteria need experienced human operators. AI can free up people, so that they can see the whole wood, not just the individual trees.

AI has a role to play in disaster recovery, especially for larger and more complex installations, on condition that it is used intelligently and with people, rather than instead of them.